Development of issue sets from social big data: A case study of green energy and low-carbon

Chun Che Huang, Yu Jie Fang, Shian Hua Lin, Wen Yau Liang, Shu Rong Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

“Energy” has been one element of the development of human civilization, also a power for national industry, construction and economic development. The green energy has become the cornerstone in sustainable development to secure such energy supply but may accommodate opinions from controversial perspectives when this subject is discussed. This study develops an interactive big data system, which aims at aggregating data from Facebook, PTT, news, and provides an interactive interface for energy domain experts. The “interaction” characterizes the seamless integration between users and the system to construct the controversial issue sets of energy, which could be identified and established autonomously in this study. The approach using tags of the link in two controversial issues can help end-users effectively query on demand. The energy relevant issues can be fully aware and provided to the decision makers from the positive and negative viewpoints.

Original languageEnglish
Title of host publicationAdvances in Data Mining
Subtitle of host publicationApplications and Theoretical Aspects - 16th Industrial Conference, ICDM 2016, Proceedings
EditorsPetra Perner
PublisherSpringer Verlag
Pages139-153
Number of pages15
ISBN (Print)9783319415604
DOIs
Publication statusPublished - 2016 Jan 1
Event16th Industrial Conference on Advances in Data Mining, ICDM 2016 - New York, United States
Duration: 2016 Jul 132016 Jul 17

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9728
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other16th Industrial Conference on Advances in Data Mining, ICDM 2016
CountryUnited States
CityNew York
Period16-07-1316-07-17

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Huang, C. C., Fang, Y. J., Lin, S. H., Liang, W. Y., & Wu, S. R. (2016). Development of issue sets from social big data: A case study of green energy and low-carbon. In P. Perner (Ed.), Advances in Data Mining: Applications and Theoretical Aspects - 16th Industrial Conference, ICDM 2016, Proceedings (pp. 139-153). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9728). Springer Verlag. https://doi.org/10.1007/978-3-319-41561-1_11